优化工具箱™提供用于查找最小化或最大化目标的参数的功能,同时满足约束。该工具箱包括线性编程(LP),混合整数线性编程(MILP),二次编程(QP),二阶锥编程(SOCP),非线性编程(NLP),约束线性最小二乘,非线性最小二乘法,非线性最小二乘法,和非线性方程。
您可以以编程方式或应用程序使用函数和矩阵定义优化问题。或者,您可以使用反映底层数学的优化变量的表达式。您可以使用客观和约束函数的自动分化,以实现更快更准确的解决方案。万博 尤文图斯
Optimization Toolbox™ provides solvers for finding a maximum or a minimum of an objective function subject to constraints. This enables you to find optimal designs, minimize risk for financial applications, optimize decision making, and estimate parameters.
You can use the problem-based approach to define the optimization variables and their bounds, set the objective, and then solve. On this problem, the solve function recognizes the problem is nonlinear, applies a nonlinear solver, and uses automatic differentiation for faster gradient evaluations.
优化问题通常具有在该生产计划问题中的变量或约束。您可以定义优化变量和约束的数组,以及使用数字或字符串的索引,从而导致大问题的可读性和紧凑的表示。
You can use the problem-based approach even when some functions are not naturally expressed as optimization expressions. This problem’s objective function requires solving an ODE. We can convert this to an optimization expression and use it in the problem to be optimized.
You can add integer constraints to linear problems involving variables which must take on integer values. This includes when the variables represent a yes or no decision, like whether a process is assigned to a processor in this scheduling example.
In addition to solvers for nonlinear, linear, and mixed-integer linear programs, Optimization Toolbox includes specialized solvers for quadratic programs, second-order cone programs, multiobjective, and linear and nonlinear least squares.
您可以快速解决数千个变量的大而稀疏问题。这里,大约三十秒内解决了超过40,000个变量的二次问题。
As an alternative to the problem-based approach, you can use Optimization Toolbox with the solver-based approach. After representing your objectives and constraints as MATLAB functions and matrices, the Optimize Live Task helps guide you through this approach by indicating where to select a solver and insert your predefined MATLAB constructs.
优化工具箱与其他MATLAB一起配合使用®tools. You can accelerate numerical gradient calculations using Parallel Computing Toolbox™.
You can compile your applications into apps or libraries with MATLAB Compiler™ and MATLAB Compiler SDK™.
You can generate portable and readable C/C++ code to solve your optimization problems using MATLAB Coder™. Use this code to deploy applications to enterprise and embedded systems.
For more information, return to the Optimization Toolbox page or choose a link below.
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